Track bundled vendor runtime sources
This commit is contained in:
645
vendor/ComfyUI/comfy_api_nodes/nodes_veo2.py
vendored
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645
vendor/ComfyUI/comfy_api_nodes/nodes_veo2.py
vendored
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@@ -0,0 +1,645 @@
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import base64
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from io import BytesIO
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from typing_extensions import override
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from comfy_api.latest import IO, ComfyExtension, Input, InputImpl
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from comfy_api_nodes.apis.veo import (
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VeoGenVidPollRequest,
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VeoGenVidPollResponse,
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VeoGenVidRequest,
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VeoGenVidResponse,
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VeoRequestInstance,
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VeoRequestInstanceImage,
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VeoRequestParameters,
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)
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from comfy_api_nodes.util import (
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ApiEndpoint,
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download_url_to_video_output,
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poll_op,
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sync_op,
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tensor_to_base64_string,
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)
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AVERAGE_DURATION_VIDEO_GEN = 32
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MODELS_MAP = {
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"veo-2.0-generate-001": "veo-2.0-generate-001",
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"veo-3.1-generate": "veo-3.1-generate-001",
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"veo-3.1-fast-generate": "veo-3.1-fast-generate-001",
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"veo-3.1-lite": "veo-3.1-lite-generate-001",
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"veo-3.0-generate-001": "veo-3.0-generate-001",
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"veo-3.0-fast-generate-001": "veo-3.0-fast-generate-001",
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}
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class VeoVideoGenerationNode(IO.ComfyNode):
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"""
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Generates videos from text prompts using Google's Veo API.
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This node can create videos from text descriptions and optional image inputs,
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with control over parameters like aspect ratio, duration, and more.
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"""
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="VeoVideoGenerationNode",
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display_name="Google Veo 2 Video Generation",
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category="partner/video/Veo",
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description="Generates videos from text prompts using Google's Veo 2 API",
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inputs=[
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IO.String.Input(
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"prompt",
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multiline=True,
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default="",
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tooltip="Text description of the video",
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),
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IO.Combo.Input(
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"aspect_ratio",
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options=["16:9", "9:16"],
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default="16:9",
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tooltip="Aspect ratio of the output video",
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),
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IO.String.Input(
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"negative_prompt",
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multiline=True,
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default="",
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tooltip="Negative text prompt to guide what to avoid in the video",
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optional=True,
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),
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IO.Int.Input(
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"duration_seconds",
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default=5,
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min=5,
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max=8,
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step=1,
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display_mode=IO.NumberDisplay.number,
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tooltip="Duration of the output video in seconds",
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optional=True,
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),
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IO.Boolean.Input(
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"enhance_prompt",
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default=True,
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tooltip="Whether to enhance the prompt with AI assistance",
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optional=True,
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advanced=True,
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),
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IO.Combo.Input(
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"person_generation",
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options=["ALLOW", "BLOCK"],
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default="ALLOW",
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tooltip="Whether to allow generating people in the video",
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optional=True,
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advanced=True,
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),
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IO.Int.Input(
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"seed",
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default=0,
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min=0,
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max=0xFFFFFFFF,
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step=1,
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display_mode=IO.NumberDisplay.number,
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control_after_generate=True,
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tooltip="Seed for video generation (0 for random)",
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optional=True,
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),
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IO.Image.Input(
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"image",
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tooltip="Optional reference image to guide video generation",
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optional=True,
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),
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IO.Combo.Input(
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"model",
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options=["veo-2.0-generate-001"],
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default="veo-2.0-generate-001",
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tooltip="Veo 2 model to use for video generation",
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optional=True,
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),
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],
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outputs=[
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IO.Video.Output(),
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],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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price_badge=IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["duration_seconds"]),
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expr="""{"type":"usd","usd": 0.5 * widgets.duration_seconds}""",
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),
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)
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@classmethod
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async def execute(
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cls,
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prompt,
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aspect_ratio="16:9",
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negative_prompt="",
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duration_seconds=5,
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enhance_prompt=True,
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person_generation="ALLOW",
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seed=0,
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image=None,
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model="veo-2.0-generate-001",
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generate_audio=False,
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):
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model = MODELS_MAP[model]
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# Prepare the instances for the request
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instances = []
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instance = {"prompt": prompt}
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# Add image if provided
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if image is not None:
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image_base64 = tensor_to_base64_string(image)
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if image_base64:
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instance["image"] = {"bytesBase64Encoded": image_base64, "mimeType": "image/png"}
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instances.append(instance)
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# Create parameters dictionary
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parameters = {
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"aspectRatio": aspect_ratio,
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"personGeneration": person_generation,
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"durationSeconds": duration_seconds,
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"enhancePrompt": enhance_prompt,
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}
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# Add optional parameters if provided
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if negative_prompt:
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parameters["negativePrompt"] = negative_prompt
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if seed > 0:
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parameters["seed"] = seed
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# Only add generateAudio for Veo 3 models
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if model.find("veo-2.0") == -1:
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parameters["generateAudio"] = generate_audio
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# force "enhance_prompt" to True for Veo3 models
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parameters["enhancePrompt"] = True
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initial_response = await sync_op(
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cls,
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ApiEndpoint(path=f"/proxy/veo/{model}/generate", method="POST"),
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response_model=VeoGenVidResponse,
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data=VeoGenVidRequest(
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instances=instances,
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parameters=parameters,
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),
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)
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def status_extractor(response):
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# Only return "completed" if the operation is done, regardless of success or failure
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# We'll check for errors after polling completes
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return "completed" if response.done else "pending"
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poll_response = await poll_op(
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cls,
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ApiEndpoint(path=f"/proxy/veo/{model}/poll", method="POST"),
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response_model=VeoGenVidPollResponse,
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status_extractor=status_extractor,
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data=VeoGenVidPollRequest(
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operationName=initial_response.name,
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),
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poll_interval=5.0,
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estimated_duration=AVERAGE_DURATION_VIDEO_GEN,
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)
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# Now check for errors in the final response
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# Check for error in poll response
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if poll_response.error:
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raise Exception(f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})")
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# Check for RAI filtered content
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if (
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hasattr(poll_response.response, "raiMediaFilteredCount")
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and poll_response.response.raiMediaFilteredCount > 0
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):
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# Extract reason message if available
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if (
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hasattr(poll_response.response, "raiMediaFilteredReasons")
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and poll_response.response.raiMediaFilteredReasons
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):
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reason = poll_response.response.raiMediaFilteredReasons[0]
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error_message = f"Content filtered by Google's Responsible AI practices: {reason} ({poll_response.response.raiMediaFilteredCount} videos filtered.)"
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else:
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error_message = f"Content filtered by Google's Responsible AI practices ({poll_response.response.raiMediaFilteredCount} videos filtered.)"
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raise Exception(error_message)
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# Extract video data
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if (
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poll_response.response
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and hasattr(poll_response.response, "videos")
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and poll_response.response.videos
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and len(poll_response.response.videos) > 0
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):
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video = poll_response.response.videos[0]
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# Check if video is provided as base64 or URL
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if hasattr(video, "bytesBase64Encoded") and video.bytesBase64Encoded:
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return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(base64.b64decode(video.bytesBase64Encoded))))
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if hasattr(video, "gcsUri") and video.gcsUri:
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return IO.NodeOutput(await download_url_to_video_output(video.gcsUri))
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raise Exception("Video returned but no data or URL was provided")
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raise Exception("Video generation completed but no video was returned")
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class Veo3VideoGenerationNode(IO.ComfyNode):
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"""Generates videos from text prompts using Google's Veo 3 API."""
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="Veo3VideoGenerationNode",
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display_name="Google Veo 3 Video Generation",
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category="partner/video/Veo",
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description="Generates videos from text prompts using Google's Veo 3 API",
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inputs=[
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IO.String.Input(
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"prompt",
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multiline=True,
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default="",
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tooltip="Text description of the video",
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),
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IO.Combo.Input(
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"aspect_ratio",
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options=["16:9", "9:16"],
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default="16:9",
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tooltip="Aspect ratio of the output video",
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),
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IO.Combo.Input(
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"resolution",
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options=["720p", "1080p", "4k"],
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default="720p",
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tooltip="Output video resolution. 4K is not available for veo-3.1-lite and veo-3.0 models.",
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optional=True,
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),
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IO.String.Input(
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"negative_prompt",
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multiline=True,
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default="",
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tooltip="Negative text prompt to guide what to avoid in the video",
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optional=True,
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),
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IO.Int.Input(
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"duration_seconds",
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default=8,
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min=4,
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max=8,
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step=2,
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display_mode=IO.NumberDisplay.number,
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tooltip="Duration of the output video in seconds",
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optional=True,
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),
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IO.Boolean.Input(
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"enhance_prompt",
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default=True,
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tooltip="This parameter is deprecated and ignored.",
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optional=True,
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advanced=True,
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),
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IO.Combo.Input(
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"person_generation",
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options=["ALLOW", "BLOCK"],
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default="ALLOW",
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tooltip="Whether to allow generating people in the video",
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optional=True,
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advanced=True,
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),
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IO.Int.Input(
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"seed",
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default=0,
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min=0,
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max=0xFFFFFFFF,
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step=1,
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display_mode=IO.NumberDisplay.number,
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control_after_generate=True,
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tooltip="Seed for video generation (0 for random)",
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optional=True,
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),
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IO.Image.Input(
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"image",
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tooltip="Optional reference image to guide video generation",
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optional=True,
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),
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IO.Combo.Input(
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"model",
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options=[
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"veo-3.1-generate",
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"veo-3.1-fast-generate",
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"veo-3.1-lite",
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"veo-3.0-generate-001",
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"veo-3.0-fast-generate-001",
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],
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tooltip="Veo 3 model to use for video generation",
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optional=True,
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),
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IO.Boolean.Input(
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"generate_audio",
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default=False,
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tooltip="Generate audio for the video. Supported by all Veo 3 models.",
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optional=True,
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),
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],
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outputs=[
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IO.Video.Output(),
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],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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price_badge=IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "resolution", "duration_seconds"]),
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expr="""
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(
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$m := widgets.model;
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$r := widgets.resolution;
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$a := widgets.generate_audio;
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$seconds := widgets.duration_seconds;
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$pps :=
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$contains($m, "lite")
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? ($r = "1080p" ? ($a ? 0.08 : 0.05) : ($a ? 0.05 : 0.03))
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: $contains($m, "3.1-fast")
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? ($r = "4k" ? ($a ? 0.30 : 0.25) : $r = "1080p" ? ($a ? 0.12 : 0.10) : ($a ? 0.10 : 0.08))
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: $contains($m, "3.1-generate")
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? ($r = "4k" ? ($a ? 0.60 : 0.40) : ($a ? 0.40 : 0.20))
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: $contains($m, "3.0-fast")
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? ($a ? 0.15 : 0.10)
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: ($a ? 0.40 : 0.20);
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{"type":"usd","usd": $pps * $seconds}
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||||
)
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""",
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||||
),
|
||||
)
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||||
|
||||
@classmethod
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||||
async def execute(
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||||
cls,
|
||||
prompt,
|
||||
aspect_ratio="16:9",
|
||||
resolution="720p",
|
||||
negative_prompt="",
|
||||
duration_seconds=8,
|
||||
enhance_prompt=True,
|
||||
person_generation="ALLOW",
|
||||
seed=0,
|
||||
image=None,
|
||||
model="veo-3.0-generate-001",
|
||||
generate_audio=False,
|
||||
):
|
||||
if resolution == "4k" and ("lite" in model or "3.0" in model):
|
||||
raise Exception("4K resolution is not supported by the veo-3.1-lite or veo-3.0 models.")
|
||||
|
||||
model = MODELS_MAP[model]
|
||||
|
||||
instances = [{"prompt": prompt}]
|
||||
if image is not None:
|
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image_base64 = tensor_to_base64_string(image)
|
||||
if image_base64:
|
||||
instances[0]["image"] = {"bytesBase64Encoded": image_base64, "mimeType": "image/png"}
|
||||
|
||||
parameters = {
|
||||
"aspectRatio": aspect_ratio,
|
||||
"personGeneration": person_generation,
|
||||
"durationSeconds": duration_seconds,
|
||||
"enhancePrompt": True,
|
||||
"generateAudio": generate_audio,
|
||||
}
|
||||
if negative_prompt:
|
||||
parameters["negativePrompt"] = negative_prompt
|
||||
if seed > 0:
|
||||
parameters["seed"] = seed
|
||||
if "veo-3.1" in model:
|
||||
parameters["resolution"] = resolution
|
||||
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/veo/{model}/generate", method="POST"),
|
||||
response_model=VeoGenVidResponse,
|
||||
data=VeoGenVidRequest(
|
||||
instances=instances,
|
||||
parameters=parameters,
|
||||
),
|
||||
)
|
||||
|
||||
poll_response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/veo/{model}/poll", method="POST"),
|
||||
response_model=VeoGenVidPollResponse,
|
||||
status_extractor=lambda r: "completed" if r.done else "pending",
|
||||
data=VeoGenVidPollRequest(operationName=initial_response.name),
|
||||
poll_interval=9.0,
|
||||
estimated_duration=AVERAGE_DURATION_VIDEO_GEN,
|
||||
)
|
||||
|
||||
if poll_response.error:
|
||||
raise Exception(f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})")
|
||||
|
||||
response = poll_response.response
|
||||
filtered_count = response.raiMediaFilteredCount
|
||||
if filtered_count:
|
||||
reasons = response.raiMediaFilteredReasons or []
|
||||
reason_part = f": {reasons[0]}" if reasons else ""
|
||||
raise Exception(
|
||||
f"Content blocked by Google's Responsible AI filters{reason_part} "
|
||||
f"({filtered_count} video{'s' if filtered_count != 1 else ''} filtered)."
|
||||
)
|
||||
|
||||
if response.videos:
|
||||
video = response.videos[0]
|
||||
if video.bytesBase64Encoded:
|
||||
return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(base64.b64decode(video.bytesBase64Encoded))))
|
||||
if video.gcsUri:
|
||||
return IO.NodeOutput(await download_url_to_video_output(video.gcsUri))
|
||||
raise Exception("Video returned but no data or URL was provided")
|
||||
raise Exception("Video generation completed but no video was returned")
|
||||
|
||||
|
||||
class Veo3FirstLastFrameNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="Veo3FirstLastFrameNode",
|
||||
display_name="Google Veo 3 First-Last-Frame to Video",
|
||||
category="partner/video/Veo",
|
||||
description="Generate video using prompt and first and last frames.",
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Text description of the video",
|
||||
),
|
||||
IO.String.Input(
|
||||
"negative_prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Negative text prompt to guide what to avoid in the video",
|
||||
),
|
||||
IO.Combo.Input("resolution", options=["720p", "1080p", "4k"]),
|
||||
IO.Combo.Input(
|
||||
"aspect_ratio",
|
||||
options=["16:9", "9:16"],
|
||||
default="16:9",
|
||||
tooltip="Aspect ratio of the output video",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=8,
|
||||
min=4,
|
||||
max=8,
|
||||
step=2,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Duration of the output video in seconds",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=0xFFFFFFFF,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed for video generation",
|
||||
),
|
||||
IO.Image.Input("first_frame", tooltip="Start frame"),
|
||||
IO.Image.Input("last_frame", tooltip="End frame"),
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=["veo-3.1-generate", "veo-3.1-fast-generate", "veo-3.1-lite"],
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"generate_audio",
|
||||
default=True,
|
||||
tooltip="Generate audio for the video.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Video.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "duration", "resolution"]),
|
||||
expr="""
|
||||
(
|
||||
$m := widgets.model;
|
||||
$r := widgets.resolution;
|
||||
$ga := widgets.generate_audio;
|
||||
$seconds := widgets.duration;
|
||||
$pps :=
|
||||
$contains($m, "lite")
|
||||
? ($r = "1080p" ? ($ga ? 0.08 : 0.05) : ($ga ? 0.05 : 0.03))
|
||||
: $contains($m, "fast")
|
||||
? ($r = "4k" ? ($ga ? 0.30 : 0.25) : $r = "1080p" ? ($ga ? 0.12 : 0.10) : ($ga ? 0.10 : 0.08))
|
||||
: ($r = "4k" ? ($ga ? 0.60 : 0.40) : ($ga ? 0.40 : 0.20));
|
||||
{"type":"usd","usd": $pps * $seconds}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
negative_prompt: str,
|
||||
resolution: str,
|
||||
aspect_ratio: str,
|
||||
duration: int,
|
||||
seed: int,
|
||||
first_frame: Input.Image,
|
||||
last_frame: Input.Image,
|
||||
model: str,
|
||||
generate_audio: bool,
|
||||
):
|
||||
if "lite" in model and resolution == "4k":
|
||||
raise Exception("4K resolution is not supported by the veo-3.1-lite model.")
|
||||
|
||||
model = MODELS_MAP[model]
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/veo/{model}/generate", method="POST"),
|
||||
response_model=VeoGenVidResponse,
|
||||
data=VeoGenVidRequest(
|
||||
instances=[
|
||||
VeoRequestInstance(
|
||||
prompt=prompt,
|
||||
image=VeoRequestInstanceImage(
|
||||
bytesBase64Encoded=tensor_to_base64_string(first_frame), mimeType="image/png"
|
||||
),
|
||||
lastFrame=VeoRequestInstanceImage(
|
||||
bytesBase64Encoded=tensor_to_base64_string(last_frame), mimeType="image/png"
|
||||
),
|
||||
),
|
||||
],
|
||||
parameters=VeoRequestParameters(
|
||||
aspectRatio=aspect_ratio,
|
||||
personGeneration="ALLOW",
|
||||
durationSeconds=duration,
|
||||
enhancePrompt=True, # cannot be False for Veo3
|
||||
seed=seed,
|
||||
generateAudio=generate_audio,
|
||||
negativePrompt=negative_prompt,
|
||||
resolution=resolution,
|
||||
),
|
||||
),
|
||||
)
|
||||
poll_response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/veo/{model}/poll", method="POST"),
|
||||
response_model=VeoGenVidPollResponse,
|
||||
status_extractor=lambda r: "completed" if r.done else "pending",
|
||||
data=VeoGenVidPollRequest(
|
||||
operationName=initial_response.name,
|
||||
),
|
||||
poll_interval=9.0,
|
||||
estimated_duration=AVERAGE_DURATION_VIDEO_GEN,
|
||||
)
|
||||
|
||||
if poll_response.error:
|
||||
raise Exception(f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})")
|
||||
|
||||
response = poll_response.response
|
||||
filtered_count = response.raiMediaFilteredCount
|
||||
if filtered_count:
|
||||
reasons = response.raiMediaFilteredReasons or []
|
||||
reason_part = f": {reasons[0]}" if reasons else ""
|
||||
raise Exception(
|
||||
f"Content blocked by Google's Responsible AI filters{reason_part} "
|
||||
f"({filtered_count} video{'s' if filtered_count != 1 else ''} filtered)."
|
||||
)
|
||||
|
||||
if response.videos:
|
||||
video = response.videos[0]
|
||||
if video.bytesBase64Encoded:
|
||||
return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(base64.b64decode(video.bytesBase64Encoded))))
|
||||
if video.gcsUri:
|
||||
return IO.NodeOutput(await download_url_to_video_output(video.gcsUri))
|
||||
raise Exception("Video returned but no data or URL was provided")
|
||||
raise Exception("Video generation completed but no video was returned")
|
||||
|
||||
|
||||
class VeoExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
return [
|
||||
VeoVideoGenerationNode,
|
||||
Veo3VideoGenerationNode,
|
||||
Veo3FirstLastFrameNode,
|
||||
]
|
||||
|
||||
|
||||
async def comfy_entrypoint() -> VeoExtension:
|
||||
return VeoExtension()
|
||||
Reference in New Issue
Block a user